Optimizing dispatch for a concentrated solar power tower

被引:39
作者
Wagner, Michael J. [1 ]
Hamilton, William T. [2 ]
Newman, Alexandra [2 ]
Dent, Jolyon [3 ]
Diep, Charles [3 ]
Braun, Robert [2 ]
机构
[1] Natl Renewable Energy Lab, Thermal Sci Grp, 15013 Denver West Pkwy, Golden, CO 80401 USA
[2] Colorado Sch Mines, Dept Mech Engn, 1500 Illinois St, Golden, CO 80401 USA
[3] SolarReserve, Financial & Performance Anal Grp, 520 Broadway, Santa Monica, CA 90401 USA
基金
美国能源部;
关键词
Concentrated solar power; Dispatch scheduling; Optimization applications; ENERGY; OPTIMIZATION; DESIGN; SYSTEM; GENERATION; CYCLES; PLANS; FIELD;
D O I
10.1016/j.solener.2018.06.093
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Concentrating solar power (CSP) systems employ a sophisticated thermal receiver, power cycle, and a heliostat field, comprised of thousands of mirrors spread over hundreds of acres of land, and are most cost-effective with relatively large quantities of energy storage which can be scheduled for dispatch. We exercise an existing optimization model that maximizes revenue over a year-long time horizon, solved using a standard 48-h look-ahead policy at hourly fidelity on a CSP system under development in California. The system employs molten salt power tower technology with a 150 MWe (net) turbine, eight hours of thermal storage at full load, and a solar field that provides 1.75 times the rated turbine thermal power. The model considers system configuration and interoperability aspects, such as storage tank size, production capacities, and ramp rates, and determines decisions that expedite financing, permitting, and plant design. Relative to results achieved via industry practice, the existing optimization model reduces the number of power cycle (i.e., turbine) start-up events by 86.4%, thereby improving net revenue by more than 8.5% annually; this corresponds to an approximately $140 M increase in net revenue over the lifetime of the plant, taking a step towards advancing the long-term economic viability of large-scale renewable energy systems. Sensitivity analysis on uncertain parameter values provides insight regarding those values that influence profit most significantly.
引用
收藏
页码:1198 / 1211
页数:14
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